Guannan Qu

1.7k citations
36 papers · 945 indexed · 1 hit paper · h-index 14
Topics
Smart Grid Energy Management (11 papers)Optimal Power Flow Distribution (11 papers)Microgrid Control and Optimization (11 papers)
Partner nations
United StatesChinaSweden

In The Last Decade

Guannan Qu

34 papers receiving 910 citations

Hit Papers

Reinforcement Learning for Selective Key Applications in ...2022202620232024202250100150200

Peers

Guannan Qu
Comparison fields: 5 of 58
  • Electrical and Electronic Engineering 664
  • Control and Systems Engineering 459
  • Computer Networks and Communications 183
  • Automotive Engineering 150
  • Artificial Intelligence 121
Replace Andrey Bernstein with:
Andrey Bernstein United States
Yujie Tang United States
Andrea Benigni Germany
Sambuddha Chakrabarti United States
Atsushi Ishigame Japan
V. P. Meena India
Yinhong Li China
Raphaël Caire France
Jie Duan China
Izudin Džafić Bosnia and Herzegovina
Guannan Qu relative to Andrey Bernstein United States Andrey Bernstein's profile →
Citations per field
00.5×4.1×
Andrey Bernstein · 1×
Citations per year

Countries citing papers authored by Guannan Qu

Since Specialization
Citations

This map shows the geographic impact of Guannan Qu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Guannan Qu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guannan Qu more than expected).

Fields of papers citing papers by Guannan Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guannan Qu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Guannan Qu. The network helps show where Guannan Qu may publish in the future.

Co-authorship network of co-authors of Guannan Qu

This figure shows the co-authorship network connecting the top 25 collaborators of Guannan Qu. A scholar is included among the top collaborators of Guannan Qu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Guannan Qu. Guannan Qu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 3
2 1
3 7
4 12
5 0
6 5
7 7
8 23
9 2
10 1
11
Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward
2
12 3
13 53
14 26
15 1
16 85
17 24
18 13
19 9
20 2

About Guannan Qu

Guannan Qu is a scholar working on Control and Systems Engineering, Computer Networks and Communications and Management Science and Operations Research, having authored 36 papers that have together received 945 indexed citations. Recurring topics across this work include Smart Grid Energy Management (11 papers), Optimal Power Flow Distribution (11 papers) and Microgrid Control and Optimization (11 papers). The work is most often cited by research in Control and Systems Engineering (459 citations), Automotive Engineering (150 citations) and Energy Engineering and Power Technology (38 citations). Guannan Qu has collaborated with scholars based in United States, China and Sweden. Frequent co-authors include Na Li, Steven H. Low, Yujie Tang, Xin Chen, Munther A. Dahleh, Bo Sun, Danny H. K. Tsang, Xiaoqi Tan, Sindri Magnússon and Yingying Li. Their work appears in journals such as IEEE Transactions on Automatic Control, Automatica and IEEE Transactions on Power Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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